class_docstr: Squared pearson correlation (r^2) metric.
class_docstr_tok: ["Squared","pearson","correlation","(","r^2",")","metric","."]
docstr: Initializes squared pearson correlation (r^2) metric.
  
  Args:
    name: Metric name.
docstr_tok: ["Initializes","squared","pearson","correlation","(","r^2",")","metric",".","Args",":","name",":","Metric","name","."]
code: def __init__(self, name: str = SQUARED_PEARSON_CORRELATION_NAME):
      """Initializes squared pearson correlation (r^2) metric.
  
      Args:
        name: Metric name.
      """
      super().__init__(
          metric_util.merge_per_key_computations(
              _squared_pearson_correlation
          ),
          name=name,
      )
  
file_path: model-analysis/tensorflow_model_analysis/metrics/squared_pearson_correlation.py
imports: from typing import Dict, Iterable, Optional
  import apache_beam
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 1 to create a new SquaredPearsonCorrelation object from inherited base classes: metric_types with example: obj = SquaredPearsonCorrelation(name)